TY - GEN
T1 - Decentralized subspace tracking via gossiping
AU - Li, Lin
AU - Li, Xiao
AU - Scaglione, Anna
AU - Manton, Jonathan H.
PY - 2010
Y1 - 2010
N2 - We consider a fully decentralized model for adaptively tracking the signal's principal subspace, which arises in multi-sensor array detection and estimation problems. Our objective is to equip the network of dispersed sensors with a primitive for online spectrum sensing, which does not require a central fusion node. In this model, each node updates its local subspace estimate with its received data and a weighted average of the neighbors' data. The quality of the estimate is measured by the total subspace mismatch of the individual subspace component estimates, which converge asymptotically in the Lyapunov sense.
AB - We consider a fully decentralized model for adaptively tracking the signal's principal subspace, which arises in multi-sensor array detection and estimation problems. Our objective is to equip the network of dispersed sensors with a primitive for online spectrum sensing, which does not require a central fusion node. In this model, each node updates its local subspace estimate with its received data and a weighted average of the neighbors' data. The quality of the estimate is measured by the total subspace mismatch of the individual subspace component estimates, which converge asymptotically in the Lyapunov sense.
UR - http://www.scopus.com/inward/record.url?scp=77955363844&partnerID=8YFLogxK
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U2 - 10.1007/978-3-642-13651-1_10
DO - 10.1007/978-3-642-13651-1_10
M3 - Conference contribution
AN - SCOPUS:77955363844
SN - 3642136508
SN - 9783642136504
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 130
EP - 143
BT - Distributed Computing in Sensor Systems - 6th IEEE International Conference, DCOSS 2010, Proceedings
T2 - 6th IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2010
Y2 - 21 June 2010 through 23 June 2010
ER -